Job Description

Job

Title

: Lead Data & Machine Learning Architect

Location

: Yate (On-Site 2 Days Per Week)

Salary

: Up to 60,000 (Depending on Experience)

Overview of Business:

This is a chance to join a team who are creating an Energy Management Solutions to minimise energy cost & increase higher returns from energy assets.



We are seeking a highly skilled Lead Data & Machine Learning Architect to design and lead the development of robust data and machine learning systems.




You will take ownership of the data architecture, drive the development and deployment of machine learning models, and contribute to the strategic use of data across the organisation.

Key Responsibilities:

Data Architecture

Schema & Model Ownership:

Design, implement, and maintain logical and physical data models, primarily using PostgreSQL.

Data Integration:

Build and manage robust data pipelines to ingest, clean, and unify data from APIs, sensors, and other external sources, using tools like Dagster.

System Design:

Select appropriate storage and processing technologies tailored to system needs.

Governance & Security:

Define and enforce data governance policies, ensuring compliance with standards such as GDPR.

Performance & Scalability:

Ensure data infrastructure is optimised for performance and can scale with growing data demands.

Machine Learning

Model Development:

Lead the development of machine learning models, particularly for time-series forecasting (e.g., predicting on-site energy production).

Data Preparation:

Manage the transformation and preparation of datasets for model training and evaluation.

Experimentation:

Design and execute experiments, tune hyperparameters, and iterate on models to improve performance.

Deployment & Monitoring:

Deploy models into production environments and monitor their ongoing performance.

Maintenance:

Establish retraining workflows and manage model updates as systems and data evolve.

Cross-functional Collaboration

Project Engagement:

Work closely with project managers and stakeholders to align data and ML capabilities with new features and strategic initiatives.

Requirements Gathering:

Collaborate with business teams to define clear, actionable requirements for data pipelines, storage solutions, and ML workflows.
If you are interested, please apply with your latest CV and we will be in touch.